========================================================================= 
Log Path: ./log/logmain.log 
Program Path: /Users/yorke/Dropbox/dissertation/3_Empirics/2_Code/vote_mobilization_code/replication/02_rep_maintext.R 
Working Directory: /Users/yorke/Dropbox/dissertation/3_Empirics/2_Code/vote_mobilization_code/replication 
User Name: yorke 
R Version: 4.3.1 (2023-06-16) 
Machine: AS23C1Q05N arm64 
Operating System: Darwin 21.6.0 Darwin Kernel Version 21.6.0: Mon Aug 22 20:20:05 PDT 2022; root:xnu-8020.140.49~2/RELEASE_ARM64_T8101 
Base Packages: stats graphics grDevices utils datasets methods base 
Other Packages: tidylog_1.1.0 MASS_7.3-60 vdemdata_13.0 xtable_1.8-4 logr_1.3.8 common_1.1.3 sandwich_3.0-2 stargazer_5.2.3 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1 tidyverse_2.0.0 
Log Start Time: 2024-06-03 17:25:20.921005 
========================================================================= 

> #### Replication Code for:
> #### Constituency Service and Electoral Accountability in Autocratic Legislatures
> #### Author: Erin York
> #### Created: 5/30/2024
> 
> # this code replicates all data-generated figures and tables in the main text
> 
> rm(list = ls())
> 
> ## Load Packages
> library(tidyverse)
> library(stargazer)
> library(logr)
> 
> options("logr.autolog" = TRUE)
> 
> # Open the log
> lf <- log_open(file.path("logmain.log"))
> 
> # Send message to log
> log_code()
> 
> 
> # load data ---------------------------------------------------------------
> 
> 
> # load cross-national dataset
> country_panel<- read_csv("df_country_panel.csv")
> # load subnational data
> # politician level
> mpdat<- read_csv("df_mplevel.csv")
> # query level
> querydat<- read_csv("df_querylevel.csv")
> # party-circonscription level
> partycirc<- read_csv("df_partylevel.csv")
> # party-municipality level
> munidat<- read_csv("df_munilevel.csv")
> 
> 
> ## helper functions ------------------------------------------------------------
> 
> # for cluster bootstrapping
> block_bs <- function(clust, dat, model){
>   nclust <- length(unique(clust))
>   levels <- unique(clust)
>   samp <- as.vector(sample(levels, size = nclust, replace = T))
>   orig <- clust
>   dat2 <- plyr::ldply(lapply(samp, FUN = function(x){dat[orig == x,]}), data.frame)
>   a <- lm(as.formula(model), data = dat2)
>   return(c(coef(a)))
> }
> 
> 
> 
> # figure 1 ----------------------------------------------------------------
> 
> f1<- country_panel %>%
>   # filter to include match between legislative and ruler party
>   # remove cases with 0 legislative seats and where ruler is non-partisan
>   filter(execme == gov1me, execme != "-999", totalseats > 0) %>% 
>   # calculate seatshare for ruling party and remaining seatshare
>   mutate(seatsharegov = gov1seat/totalseats,
>          seatsharenongov = 1-seatsharegov) %>%
>   group_by(year) %>%
>   # identify average and percentiles
>   summarise(mu = mean(seatsharegov), cilo = quantile(seatsharegov, .05), cihi = quantile(seatsharegov, .95),
>             n = n()) %>%
>   ggplot(aes(x = year, y = mu)) + 
>   geom_pointrange(aes(ymin = cilo, ymax = cihi), color = "gray", size = .3) + geom_point() +
>   theme_bw() + ylim(c(0, 1)) + xlab("") + ylab("Prop. seats held by ruling party")
> f1
> 
> ggsave(f1, filename = "Figure1.pdf",
>       width = 8, height = 5)
> 
> 
> # figure 2 ----------------------------------------------------------------
> 
> # nation casework and complaint should be defined earlier
> f2<- querydat %>%
>   # province - includes both provinces and prefectures (urban equivalent)
>   mutate(Province = ifelse(provdum + prefdum > 0, 1, 0)) %>%
>   rename(Nation =natdum,
>          Region = regdum,
>          Commune = commdum,
>          Georeference = anyplace,
>          Casework = casework,
>          Complaint = complaint) %>%
>   dplyr::select(Nation, Region, Province, Commune, Georeference, Casework, Complaint) %>%
>   # generate summary statistics across query content
>   summarise_each(funs(mean)) %>%
>   gather(attribute, mn) %>%
>   mutate(type = "Written (n = 27196)") %>%
>   mutate(attribute = fct_reorder(attribute, mn),
>          rounded = round(mn, digits = 2)) %>%
>   # generate bar plot
>   ggplot(aes(x = attribute, y = mn, fill = type)) +
>   geom_bar(stat = "identity", position = "dodge") +
>   geom_text(aes(label = rounded, hjust = -.5), 
>             position = position_dodge(width = 1)) +
>   ylim(c(0, 1)) +
>   theme_bw() +
>   coord_flip() +
>   ylab("Proportion of queries with specified content reference") +
>   xlab("") +
>   guides(fill = "none") +
>   scale_fill_manual(values = c("#1F78B4"))
> f2
> 
> ggsave(f2, file = "Figure2.pdf",
>       width = 8, height = 5)
> 
> 
> # table 1 -----------------------------------------------------------------
> 
> 
> set.seed(123456)
> 
> writ1 <- lm(log_nwrit ~ royalist, data = mpdat)
> bs <- replicate(block_bs(mpdat$party_full, mpdat, writ1), n = 2000)
> se1 <- apply(bs, MARGIN = 1, FUN = sd, na.rm = T)
> 
> writ2 <- lm(log_nwrit ~ royalist + leader + natlist +
>               former + actif, data = mpdat)
> bs <- replicate(block_bs(mpdat$party_full, mpdat, writ2), n = 2000)
> se2 <- apply(bs, MARGIN = 1, FUN = sd, na.rm = T)
> 
> writ3 <- (lm(log_nwrit ~ royalist + gov_full + leader + female + youth  +
>                former + actif, data = mpdat))
> bs <- replicate(block_bs(mpdat$party_full, mpdat, writ3), n = 2000)
> se3 <- apply(bs, MARGIN = 1, FUN = sd, na.rm = T)
> 
> 
> sink("Table1.tex")
> stargazer(writ1, writ2, writ3,
>           se = list(se1,  se2,  se3),
>           dep.var.labels = "Log Written Questions",
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant"),
>           omit.stat = c("f", "ser", "adj.rsq"),
>           covariate.labels = c("Royalist", "Governing Coalition", "Committee Leader",
>                                "National List", "Female", "Youth",
>                                "2007 Parliament", "Civic Engagement"))
> sink()
> 
> ## table 2 ---------------------------------------------------------------------
> 
> 
> win3 <- (lm(delta_voteshare ~ n_wr_ln + n_or_ln + npols + region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> win4 <- (lm(delta_voteshare ~ n_wr_ln + n_or_ln + npols + factor(circid), data = partycirc))
> 
> win5 <- (lm(delta_votes ~ n_wr_ln + n_or_ln + npols  +  region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, data = partycirc))
> 
> win6 <- (lm(delta_votes ~ n_wr_ln + n_or_ln + npols  + factor(circid), data = partycirc))
> 
> sink(file = "Table2.tex")
> stargazer(win3, win4, win5, win6,
>           dep.var.labels = c("Change in Voteshare 2011-2016", "Change in Votes 2011-2016"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           
>           omit = c("Constant", "reg", "circ*",
>                    "internet", "unem", "ama", "illit", "population", "urb"),
>           covariate.labels = c("Log Written", "Log Oral",
>                                "No. District Seats"),
>           add.lines = list(c("Mean DV",  "0.00", "0.00", "2338", "2338"),
>                            c("Region FEs", "\\checkmark", "", "\\checkmark", ""),
>                            c("District Controls", "\\checkmark", "", "\\checkmark", ""),
>                            c("District FEs", "",  "\\checkmark", "", "\\checkmark")),
>           omit.stat = c("adj.rsq","f", "ser"))
> sink()
> 
> 
> ## table 3 ---------------------------------------------------------------------
> 
> roy1 <- (lm(delta_voteshare ~ n_wr_ln + 
>               region + log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban , 
>             data = filter(partycirc, royalist == 1)))
> 
> roy2 <- (lm(delta_voteshare ~ n_wr_ln +
>               region +  log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban , 
>             data = filter(partycirc, royalist == 0)))
> 
> roy3 <- (lm(delta_voteshare ~ n_wr_ln * royalist + 
>               region +  log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, 
>             data = partycirc))
> 
> roy4 <- (lm(delta_votes ~ n_wr_ln + 
>               region +  log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, 
>             data = filter(partycirc, royalist == 1)))
> 
> roy5 <- (lm(delta_votes ~ n_wr_ln +
>               region +  log(population) +
>               internet + unemployment + illiteracy + amazigh_low + urban, 
>             data = filter(partycirc, royalist == 0)))
> 
> roy6 <- (lm(delta_votes ~ n_wr_ln * royalist   +
>               region +  log(population) +
>               internet + unemployment + illiteracy +amazigh_low + urban, 
>             data = partycirc))
> 
> sink("Table3.tex")
> stargazer(roy1, roy2, roy3, roy4, roy5, roy6,
>           covariate.labels = c("Log Written", "Royalist", "Log Writ*Royalist"),
>           omit = c("Constant", "reg", "circ*", "internet", "unem", "ama", "illit", "pop*", "urb"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           dep.var.labels = c("Change in Voteshare 2011-2016", "Change in Votes 2011-2016"),
>           no.space = T,
>           omit.stat = c("adj.rsq", "f", "ser"),
>           add.lines = list(c("Sample", "Royalist", "Opposition", "All", "Royalist", "Opposition", "All"),
>                            c("Region FEs", rep("\\checkmark", 6)),
>                            c("Dem. Controls", rep("\\checkmark", 6))))
> sink()
> 
> ## table 4 ---------------------------------------------------------------------
> 
> reg4a <- lm(voteshare2015 ~ logrefpre + logpop + nparties + party_circ + seatprop09,
>             munidat)
> 
> reg4b <- lm(voteshare2015 ~ logrefpre + logpop + nparties + seatprop09 + party_circ,  
>             filter(munidat, provname == 0))
> 
> reg4c <- lm(voteshare2015 ~ loglocalpre + logpop + nparties + party_circ + seatprop09, 
>             munidat)
> 
> reg4d <- lm(voteshare2015 ~ loglocalpre + party_circ + logpop + nparties + seatprop09, 
>             filter(munidat, provname == 0))
> 
> 
> sink("Table4.tex")
> stargazer(reg4a, reg4b, reg4c, reg4d,
>           covariate.labels = c("Log References (Any)", "Log References (Local)",
>                                "Log Pop", "No. Parties", "2009 Seatshare"),
>           star.cutoffs = c(0.05, 0.01, 0.001),
>           omit = c("Constant", "party_circ"),
>           omit.stat = c("f", "ser", "adj.rsq"),
>           add.lines = list(c("Party-District FE", rep("\\checkmark", 4)),
>                            c("Unique Toponym Subset", "", "\\checkmark", "", "\\checkmark")),
>           dep.var.labels = "2015 Municipal Voteshare")
> sink()
> 
> 
> ####
> 
> log_close()
> 

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Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:26:11.181587 
NOTE: Elapsed Time: 0.0070950984954834 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:26:11.194808 
NOTE: Elapsed Time: 0.0132210254669189 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:26:11.208043 
NOTE: Elapsed Time: 0.0132350921630859 secs 

Warning: length of NULL cannot be changed 

NOTE: Log Print Time:  2024-06-03 17:26:11.215723 
NOTE: Elapsed Time: 0.00767993927001953 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:26:11.392988 
NOTE: Elapsed Time: 0.177264928817749 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:26:12.114194 
NOTE: Elapsed Time: 0.721205949783325 secs 

Warning: number of rows of result is not a multiple of vector length (arg 2) 

NOTE: Log Print Time:  2024-06-03 17:26:12.411012 
NOTE: Elapsed Time: 0.296818017959595 secs 

========================================================================= 
Log End Time: 2024-06-03 17:26:12.736696 
Log Elapsed Time: 0 00:00:51 
========================================================================= 
